In this research paper, the effectiveness and capability of remote sensing (RS) and geographic information systems (GIS) are investigated as powerful tools for analyzing changes in land use and land cover (LULC), as well as for accuracy assessment. The study employs the literature of satellite imagery and GIS data to evaluate LULC changes over a period and to assess the accuracy of the analysis. Moreover, the research investigates the land use and land cover change detection analysis using RS and GIS, application of artificial intelligence (AI), and Machine Learning (ML) in LULC classification, environment and risk evaluation, stages of process LULC classification, factors affecting the LULC classification, accuracy assessment, and potential applications of RS and GIS in predicting future LULC changes and supporting decision-making processes. The findings of the study suggest that RS and GIS are highly effective and accurate for LULC analysis and assessment, with substantial potential for predicting and managing future changes in land use and land cover. The paper emphasizes the importance of utilizing RS and GIS techniques in the field of sustainable environmental management and resource planning.

Keywords : Remote Sensing (RS); Geographic Information Systems (GIS); Land use and Land Cover (LULC); Accuracy Assessment; Scale; Resolution Effects.